Patterns for Presenting Information

Discussing Raw Data

Some college writing requires that you interpret and discuss raw data presented in a nontextual form, such as a table, graph, figure, or illustration. You might have conducted a survey and now have to report on the results. Your instructor may ask you to review the data on unemployment and discuss whether there is a correlation between national debt and unemployment data. Or you may be asked to support your position on capital punishment by citing data on recidivism in your state. In any case, your discussion of the data may be as short as the interpretation of data presented in a table or as long as the research report itself.

The organization of a data discussion usually follows the general-to-specific pattern. First, you present the main claim supported by the data. Then, you discuss the details as they support or deny the main claim. Your discussion may include the problems, implications, exceptions, methodologies, and so on. Interpreting and commenting on data require clear thinking on your part, reflected in a clear thesis with specific supporting ideas for your interpretation of the data.

When asked to write this kind of an assignment, some students make the mistake of simply describing what the data says, rather than interpreting the data. Another mistake is reading too much into the data and drawing unreasonable conclusions. The key is “to find the right strength of claim for the data and then order your statements in some appropriate way (such as from the more significant to the less significant)” (Swales & Feak, 1994, p. 77) or from the most emphatic to the least emphatic. Each discipline has its own methods, theories, beliefs, and common practices for working with data. Talk with your instructor or review your texts for more information on interpreting data in your discipline.

Raw data is generally presented in a visual format such as a chart or graph but is generally discussed in a general-to-specific pattern.


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